from tensorforce.agents import Agent
from tensorforce.environments import Environment
# Setup environment
# (Tensorforce or custom implementation, ideally using the Environment interface)
environment = Environment.create(environment='environment.json')
# Create and initialize agent
agent = Agent.create(agent='agent.json', environment=environment)
agent.initialize()
# Reset agent and environment at the beginning of a new episode
agent.reset()
states = environment.reset()
terminal = False
# Agent-environment interaction training loop
while not terminal:
actions = agent.act(states=states)
states, terminal, reward = environment.execute(actions=actions)
agent.observe(terminal=terminal, reward=reward)
# Close agent and environment
agent.close()
environment.close()